Modeling simulation method of servo motor

Abstract

The invention relates to the technical field of three-dimensional simulation, in particular to a modeling simulation method of a servo motor. The method comprises the following steps: initializing control parameters of a servo motor; the control parameters are used for executing control direction verification, and encoder feedback signals are recorded; determining a test control direction according to the encoder feedback signal and the control parameter; servo motor design data are obtained, and a three-dimensional simulation model is constructed according to the servo motor design data; inputting a test control direction into the three-dimensional simulation model, and outputting a simulation signal of the servo motor; calculating the oscillation amplitude of the rotor according to the simulation signal; and if the oscillation amplitude of the rotor exceeds the preset oscillation amplitude, correcting the signal phase of the simulation signal, and outputting a corrected simulation signal. Modeling and simulation are carried out on the servo motor based on the three-dimensional simulation technology, the operation characteristics of the servo motor are accurately simulated, and the control precision and the test efficiency are improved through oscillation amplitude monitoring and signal correction.

Description

Technical Field

[0001] This invention relates to the field of three-dimensional simulation technology, and in particular to a modeling and simulation method for servo motors. Background Technology

[0002] In existing servo motor modeling and simulation technologies, the dynamic characteristics of servo motors are usually described by relying on theoretical mathematical models or empirical parameters. This approach can basically reflect the operating characteristics of servo motors in application scenarios where the motor structure is simple, the control direction is clear, or the operating conditions change little. However, in application environments where the structural assembly relationship is complex, the control direction needs to be verified, or the dynamic response accuracy requirement is high, the traditional servo motor modeling and simulation methods cannot guarantee the consistency between the simulation results and the actual operating state because the modeling process mainly relies on idealized assumptions, insufficient consideration of structural factors, and separation of control and structure modeling. While existing technologies can achieve basic simulation analysis of servo motors through control models or simplified structural models, they generally suffer from the following problems: First, most modeling methods only focus on the response characteristics at the control algorithm level, lacking unified modeling of the servo motor's three-dimensional structure, internal component spatial constraints, and assembly clearances, making it difficult to reflect the influence of structural factors on dynamic characteristics; Second, the control direction configuration and encoder feedback relationship usually rely on manual setting or experience judgment, without forming a systematic control direction verification mechanism, which easily leads to inconsistencies between the simulation model and the actual control direction; Third, existing simulation processes mostly take steady-state or single dynamic response as the analysis object, lacking comprehensive analysis of rotor oscillation characteristics, phase changes, and oscillation amplitude, making it difficult to support the modeling and simulation requirements of high-precision control and complex working conditions. Summary of the Invention

[0003] Therefore, it is necessary for the present invention to provide a modeling and simulation method for servo motors to solve at least one of the above-mentioned technical problems.

[0004] To achieve the above objectives, a modeling and simulation method for a servo motor includes the following steps: Step S1: Initialize the control parameters of the servo motor; perform control direction verification using the control parameters and record the encoder feedback signal; determine the test control direction based on the encoder feedback signal and the control parameters; Step S2: Obtain servo motor design data and construct a three-dimensional simulation model based on the servo motor design data; input the test control direction into the three-dimensional simulation model and output the simulation signal of the servo motor; Step S3: Calculate the rotor oscillation amplitude based on the simulation signal; if the rotor oscillation amplitude exceeds the preset oscillation amplitude, correct the signal phase of the simulation signal and output the corrected simulation signal.

[0005] The beneficial effects of this invention are as follows: (1) By verifying the control direction of the servo motor and combining it with the encoder feedback signal, the test control direction is determined, so as to achieve accurate identification of the actual control direction, provide a reliable basis for the input of the simulation model, and ensure the consistency between the simulation signal and the actual operating state of the motor.

[0006] (2) In the process of constructing the three-dimensional simulation model, based on the size of the motor housing, information of internal components and spatial constraints, rotational degrees of freedom are set and motion simulation is performed to achieve accurate modeling of the internal structure motion and assembly relationship of the motor, improve the simulation accuracy of the model for rotor rotational inertia, bearing installation position and winding space occupation, and provide complete data support for dynamic analysis and control simulation.

[0007] (3) In the simulation signal analysis stage, the dynamic response characteristics and oscillation behavior of the motor are optimized by calculating the rotor oscillation amplitude and correcting the signal phase, so as to ensure the stability and reliability of the simulation signal and improve the applicability and accuracy of the simulation model under different load and control conditions. Attached Figure Description

[0008] Other features, objects, and advantages of the invention will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings: Figure 1 This is a schematic diagram of the steps in the modeling and simulation method for a servo motor according to the present invention; Figure 2 This is a schematic diagram of the servo motor model in this invention; Figure 3 This is a structural block diagram of the terminal device in this invention; The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0009] The technical method of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without inventive effort are within the scope of protection of this invention.

[0010] Furthermore, the accompanying drawings are merely illustrative of the invention and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and therefore repeated descriptions of them will be omitted. Some block diagrams shown in the drawings are functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities can be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor methods and / or microcontroller methods.

[0011] It should be understood that although the terms "first," "second," etc., may be used herein to describe various units, these units should not be limited by these terms. These terms are used merely to distinguish one unit from another. For example, without departing from the scope of the exemplary embodiments, a first unit may be referred to as a second unit, and similarly, a second unit may be referred to as a first unit. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0012] To achieve the above objectives, please refer to Figures 1 to 3 This invention provides a modeling and simulation method for servo motors, the method comprising the following steps: Step S1: Initialize the control parameters of the servo motor; perform control direction verification using the control parameters and record the encoder feedback signal; determine the test control direction based on the encoder feedback signal and the control parameters; In one embodiment, a target control mode (such as speed closed-loop mode or position closed-loop mode) is selected on the servo motor control card. The proportional (P), integral (I), and derivative (D) parameters in the control mode are initialized to zero values ​​and saved as the initial control configuration. On the motor side, the control mode is set, and the proportional coefficient between the control signal and the motor speed is defined. The initial control configuration and proportional coefficient are used as control parameters. These parameters are then sent to the servo motor to calculate the actual rotational speed, which is compared to a preset zero-drift threshold. When the rotational speed exceeds the zero-drift threshold, the offset compensation value is adjusted to eliminate zero drift. The offset compensation value is used to determine the control direction, and the encoder feedback signal is recorded. The test control direction is determined based on the encoder feedback signal: if it is positive, the original direction is maintained; if it is negative, an inversion operation is performed. The corrected direction is written into the control parameters to determine the final test control direction.

[0013] In another embodiment, assuming a speed closed-loop mode is selected, the proportional coefficient... Integral coefficient Differential coefficients The initial zero-drift threshold was 0.4 rpm. Through encoder feedback testing, the measured speed sequence was [0.3, 0.6, 0.2, 0.5, 0.7] rpm. For frames exceeding the threshold (frames 2, 4, and 5), the automatic bias compensation values ​​were adjusted to 0.05, 0.02, and 0.03 rpm, respectively. The test control direction was determined to be 60% positive frames and 40% negative frames to ensure the simulation input direction matched the actual motor direction.

[0014] Step S2: Obtain servo motor design data and construct a three-dimensional simulation model based on the servo motor design data; input the test control direction into the three-dimensional simulation model and output the simulation signal of the servo motor; In one embodiment, servo motor design data is first acquired, including motor housing dimensions and internal component information. The motor housing outline is drawn based on the housing dimensions, and mounting holes and fixing structures are added to the outline. Assembly clearance verification is performed using the mounting holes and fixing structures, recording acceptable clearance constraints and interference risk constraints. Based on the internal component information, core, winding coil, and bearing models are constructed, and a complete three-dimensional simulation model is built by combining spatial constraint information. Subsequently, the determined test control direction is input into the simulation model, outputting speed feedback signals and current feedback signals. The speed signal is integrated, and the current signal is filtered, and the results are integrated to obtain the servo motor simulation signal.

[0015] In another embodiment, assuming the motor housing diameter is 120mm, height is 150mm, and mounting hole spacing is 50mm, assembly clearance analysis reveals 3 minor interference risks and 1 major interference risk. In the internal component modeling, the core slot number is 24, each winding coil has 15 turns, and the bearing mounting position coordinates are [x=30, y=0, z=20]mm. After inputting the test control direction into the simulation model, the speed feedback peak sequence [1500, 1520, 1480, 1510]rpm and the current feedback peak sequence [1.8, 1.9, 2.0, 1.85]A are obtained. After integration and filtering, a complete simulation signal sequence is generated, with both the speed and current curves reflecting the rotor's dynamic characteristics.

[0016] Step S3: Calculate the rotor oscillation amplitude based on the simulation signal; if the rotor oscillation amplitude exceeds the preset oscillation amplitude, correct the signal phase of the simulation signal and output the corrected simulation signal.

[0017] In one embodiment, the rotor speed and current variation curves over time are extracted from the output simulation signal, and the instantaneous change of rotor angular displacement over time is calculated using the speed curves. The oscillation amplitude within each cycle is obtained through local extremum analysis, and the oscillation amplitude is compared with a preset oscillation threshold. When comparing, If a frame is found to have excessive oscillations, a phase correction method is used to adjust it for frames exceeding a threshold. This involves calculating the phase offset based on the peak and trough positions of the current velocity curve. Shift the timing of the simulated signal forward or backward. This reduces the oscillation amplitude below the threshold, and the corrected simulation signal continues to be output, while updating the velocity curve and current curve.

[0018] In another embodiment, it is assumed that the rotor oscillation amplitude sequence calculated from the simulation signal is as follows: Preset oscillation amplitude threshold Calculate the phase offset for signals exceeding the threshold in the second and third frames respectively. The specific correction method involves shifting the velocity curve of the second frame forward by 0.25° on the time axis to correspond to the angular displacement time period, recalculating the local extremum to obtain an oscillation amplitude of 0.98°, and shifting the velocity curve of the third frame backward by 0.5° on the time axis to correspond to the angular displacement time period, recalculating the local extremum to obtain an oscillation amplitude of 0.99°. After correction, the output simulation signal velocity peak sequence is [1500, 1505, 1508, 1510] rpm, and the current peak sequence is [1.8, 1.85, 1.9, 1.85] A. The oscillation amplitude of all frames is controlled within the threshold of 1°, ensuring the stability and continuity of the rotor simulation dynamic characteristics. This method can clearly quantify the correction amount of each frame oscillation and realize oscillation monitoring, judgment, phase correction, and output closed loop during the simulation process, providing reliable data for rotor dynamics simulation and control strategy verification. Furthermore, the oscillation amplitude and correction amount can be further plotted as a heat map or time series diagram to observe the oscillation trend and can be adjusted according to simulation requirements. and To optimize rotor vibration control strategies.

[0019] Preferably, the control parameters for initializing the servo motor in step S1 include: On the control card side of the servo motor, select the target control mode, initialize the proportional, integral and derivative parameters in the target control mode to zero values, and save them as the initial control configuration; In one embodiment, assuming a speed closed-loop control mode is selected, the proportional coefficient P, integral coefficient I, and derivative coefficient D are all initialized to 0. The system writes this initial configuration into the control card's internal memory and records the control mode number and initialization timestamp for subsequent control debugging and simulation analysis. The purpose is to provide a standardized and traceable initial state for subsequent motor control, ensuring all subsequent operations are performed under a unified benchmark and avoiding the impact of historical parameter residues on control accuracy or system stability. During operation, the control card's communication status, buffer status, and motor connection status can also be recorded synchronously to provide reference data for subsequent testing or troubleshooting.

[0020] In another embodiment, assuming a position closed-loop control mode is selected, the proportional coefficient P is set to 0.05, the integral coefficient I to 0, and the derivative coefficient D to 0.01. This initial configuration is saved as a control file numbered "0002," and initialization operations are performed on three servo motors with different rated power to generate an initial control parameter list. , , Assuming the rated speeds of these motors are 1500, 1800, and 1200 rpm, respectively, after initialization, they can be used for subsequent simulation analysis to evaluate the response differences of different motor types under a unified control mode. At the same time, the initial zero-point drift of the motors and the response to small control signals can be observed in the simulation environment, providing reference data for subsequent control optimization and parameter fine-tuning.

[0021] On the servo motor side, set the control mode and the proportional coefficient between the control signal and the motor speed in the control mode; use the initial control configuration and the proportional coefficient as the control parameters of the servo motor.

[0022] In one embodiment, it is assumed that a speed closed-loop control method is set, and the proportional coefficient is... The proportional gain is set to 0.8, and the saved initial control configuration and proportional gain are sent to the motor control unit. At this point, the initial speed is read via the encoder for zero-drift verification, ensuring that the control signal and the actual motor speed exhibit the expected linear relationship, and that the system does not experience overshoot or oscillation in the initial state. This operation guarantees that the impact of the proportional gain on the speed response can be accurately quantified during subsequent control strategy testing, thus providing reliable basic data for simulation signal correction, oscillation amplitude control, and dynamic response optimization.

[0023] In another embodiment, assuming that a speed closed-loop control method is still used, but the proportional coefficient... Different values ​​were selected between 0.5 and 1.0 to evaluate the impact of different coefficients on the dynamic response of the motors. Specifically, the values ​​were set for each of the three motors. The initial control configuration is set to 0.7 and 1.0, and combined with each proportional coefficient to form a complete sequence of control parameters. It is assumed that the peak speeds measured under these conditions are 1480, 1500, and 1515 rpm, and the peak currents are 1.7, 1.85, and 1.9 A. This setting allows for the quantitative observation of the proportional coefficient variation on the rotor oscillation amplitude and speed response in a simulation environment, and can also be used to evaluate the control stability under current load variations and motor transient states.

[0024] Preferably, in step S1, the control direction verification is performed using control parameters, and the encoder feedback signal is recorded, including: The control parameters are sent to the servo motor, and the speed is calculated. The speed is compared with the preset zero drift threshold. When the speed is greater than the zero drift threshold, the offset compensation value is adjusted. The control direction is determined using the offset compensation value. In one embodiment, after the set proportional coefficient, integral coefficient, and derivative coefficient are sent to the motor control unit, the control system immediately calculates the instantaneous speed of the motor. Assuming a sampling frequency of 1kHz, the motor speed is collected every frame, and the encoder pulse count is recorded. Subsequently, the calculated speed is compared with a preset zero-drift threshold to determine if there is a slight deviation in the motor's initial state. In this embodiment, the zero-drift threshold is set to... If the motor's current speed exceeds this threshold, the offset compensation value is automatically calculated and applied to the motor controller input, thereby eliminating errors caused by initial offset. Furthermore, the offset compensation value determines the current control direction, ensuring that the motor's rotation direction at startup is consistent with the expected direction, avoiding transient reversal or jitter during startup, thus providing a stable foundation for subsequent precise control.

[0025] In another embodiment, assuming that the three servo motors, after sending control parameters, calculate their rotational speeds in real time to be 0.08, 0.04, and... The zero drift threshold is set to Therefore, the first and third motors need to have their offset compensation values ​​adjusted, while the second motor does not. Assume that after offset compensation, the compensation values ​​for the three motors are 0.02, 0, and... The control direction is determined to be positive rotation by this compensation value. During this process, the number of encoder pulses collected for each motor within a 100ms sampling window are 800, 790, and 815 pulses respectively. After offset compensation adjustment, the actual speed is stable within the preset range. This ensures the stability of the motor during the initial startup phase.

[0026] The control direction is sent to the servo motor, and the encoder feedback signal is recorded.

[0027] In one embodiment, the control system applies the calculated bias compensation value to the motor controller, causing the motor to rotate in a predetermined direction. Simultaneously, the encoder outputs a real-time pulse signal at a 1kHz sampling rate. The system calculates the instantaneous motor speed and cumulative angle based on the encoder feedback signal and compares it with the commanded control direction. If the feedback matches the commanded direction, the control direction is confirmed to be correct; otherwise, anomaly detection logic is triggered for correction. In this embodiment, it is assumed that the motor's initial response time is 20ms. After bias compensation adjustment, the speed change is smooth, and the maximum overshoot is less than 5%, ensuring the system quickly enters a stable operating state.

[0028] In another embodiment, assuming that the control direction commands received by the three motors are all positive rotation, the number of pulses collected by the encoder feedback signal in the first 100ms are 805, 792, and 818, respectively, and the calculated instantaneous speeds are 1.01, 0.99, and 1.02 rad / s, consistent with the expected control direction. By analyzing the encoder feedback of 10 consecutive frames, the bias correction effect and response stability of each motor can be observed, assuming that the maximum deviation does not exceed 0.03 rad / s.

[0029] Preferably, step S1, determining the test control direction based on the encoder feedback signal and control parameters, includes: When the encoder feedback signal is a positive feedback signal, the original control direction identifier in the control parameters is maintained; In one embodiment, after receiving control parameters, the servo motor system reads the encoder output signal in real time and compares it with the target direction. When the encoder feedback signal indicates that the motor rotation direction is consistent with the expected control direction, the control system keeps the original control direction identifier unchanged and continues to send control commands to the motor to maintain stable operation. In this embodiment, assuming the sampling frequency is 1kHz and the instantaneous motor speed is... Within a certain range, the encoder pulse is recorded once every millisecond, for a total of 1000 sampling points. Throughout the entire operation, the original direction indicator does not need to be modified, and the control signal and feedback signal remain highly consistent, thus ensuring that the servo motor starts and runs precisely in the predetermined direction, while providing reliable basic data for subsequent control tests.

[0030] In another embodiment, assuming that all three servo motors receive control commands during the initial startup phase, the encoder feedback signal shows that the first and third motors are moving in the positive direction, while the second motor is moving slightly in the negative direction (with an error of approximately...). If the first and third encoders maintain their original control direction indicators, the system records their direction indicators as 1. The second encoder, however, shows a slight reverse direction in the feedback, so its original direction indicator remains unchanged. Ten frames of encoder data were continuously collected, with the positive feedback signal occupying eight frames and an average deviation of 0.01 rad / s. This confirms that the positive signal is stable and reliable, maintaining the original direction indicator and providing reference data for multi-motor coordinated testing.

[0031] When the encoder feedback signal is a reverse feedback signal, the original control direction identifier is inverted and the corrected direction identifier is recorded. The corrected direction identifier is written into the control parameters, overwriting the original control direction identifier, in order to determine the test control direction.

[0032] In one embodiment, when the system detects that the rotation direction output by the encoder is inconsistent with the original control direction, it automatically inverts the original control direction identifier; for example, if the original identifier was 1, the modified identifier is 0. Subsequently, the direction identifier in the control parameters is overwritten, and the new corrected direction takes effect immediately to guide the motor to rotate in the correct direction. The system simultaneously records the update time of the corrected direction identifier, the corresponding encoder feedback data, and the corrected motor response to verify the effectiveness of the correction strategy and the control accuracy. In this embodiment, it is assumed that the motor's start-up delay after correction does not exceed 20ms, and the instantaneous speed deviation is controlled within 0.02rad / s, ensuring that the corrected direction takes effect quickly and the motor operates smoothly.

[0033] In another embodiment, assume that the number of frames in which the three motors generate reverse feedback signals during startup are [2, 5, 3], with the first motor generating reverse feedback in frame 2, the second in frame 5, and the third in frame 3. The system performs an inversion operation on these reverse frames, writing the corrected direction identifier into the control parameters and overwriting the original identifier. Assume that after correction, 10 consecutive frames of encoder feedback signals show that all three motors are rotating in the corrected direction, with instantaneous speeds stabilizing within the ranges of 0.99, 1.01, and 1.00 rad / s, respectively.

[0034] Preferably, step S2, which involves obtaining servo motor design data and constructing a 3D simulation model based on the servo motor design data, includes: Acquire servo motor design data, including motor housing dimensions and internal component information; draw the motor housing outline based on the motor housing dimensions, and add mounting holes and fixing structures to the motor housing outline; use the mounting holes and fixing structures to perform assembly clearance verification to record spatial constraint information; In one embodiment, the system first reads motor housing data (length, width, and height: 120mm, 80mm, and 100mm respectively) from the motor design database, along with the dimensions and layout information of internal components such as gears, bearings, and electromagnetic coils. Subsequently, a housing outline drawing is generated in CAD software, and mounting holes (6mm in diameter, four in total) and fixing slots are arranged at designated locations to support the motor. Assembly clearance verification is performed through a virtual assembly module, measuring the minimum clearance between each mounting hole and its corresponding fixing structure. Assuming the clearance range is 0.5–1.2mm, this is recorded in an assembly clearance table to determine the spatial constraints during the assembly of the housing and internal components, and to provide reference data for subsequent 3D simulation.

[0035] In another embodiment, the servo motor housing is assumed to be 140mm long, 90mm wide, and 110mm high, with six mounting holes of 6.5mm diameter each. The fixing structure includes support columns and guide grooves. During assembly clearance verification, the clearances between different hole positions and internal gears and bearings are measured through virtual assembly as [0.4mm, 0.8mm, 0.6mm, 0.9mm, 0.5mm, 1.0mm]. The system records these values ​​as spatial constraint information for subsequent simulation analysis. Furthermore, the minimum distance between the internal coil and the housing wall is assumed to be 1.5mm, and the minimum clearance between the gear and the bearing is assumed to be 0.8mm, to assess potential interference or excessive tightness during actual assembly.

[0036] An internal component model is constructed based on the internal component information; a three-dimensional simulation model is constructed using spatial constraint information and the internal component model.

[0037] In one embodiment, the system generates a 3D model based on the design parameters of components such as gears, bearings, rotors, and stators. Each component is modeled using an independent CAD solid model, while retaining material and weight attributes. Subsequently, using the obtained assembly clearance information, the internal components are placed within the outer shell contour, ensuring that the components do not interfere with each other in space. The clearances between parts in the simulation model are consistent with the actual assembly clearances; for example, the distance between the gear and the bearing is maintained at 0.8 mm, and the clearance between the bearing and the housing fixing hole is maintained at 0.6 mm. After the model is completed, a virtual assembly test can be performed on the entire motor, including rotor rotation, gear meshing, and coil layout checks, to verify the rationality of the design and the feasibility of operation.

[0038] In another embodiment, the internal component model is assumed to include a rotor, stator, six gears, three bearings, and an electromagnetic coil assembly, totaling 11 components. Based on the recorded spatial constraint information, the components are placed into the housing, and the minimum clearance obtained from the virtual simulation is [0.5mm, 0.7mm, 0.6mm, 0.9mm, 0.4mm, 0.8mm, 0.5mm, 0.6mm, 0.7mm, 0.5mm, 0.6mm]. In the simulation, the gears mesh smoothly during rotor rotation, the bearing load is evenly distributed, and the clearance between the coils and the housing is greater than 1.0mm, verifying the spatial compatibility and assembly feasibility of the design under multi-point conditions.

[0039] Preferably, assembly clearance verification is performed using mounting holes and fixing structures to record spatial constraint information, including: Determine the coordinates of the mounting holes; read the coordinates of the fixed structure; match the coordinates of the mounting holes and the fixed structure, and generate a matching directory; In one embodiment, the system first extracts the coordinates of the four mounting holes on the motor housing from the CAD model (e.g., ...). , , , ), and at the same time read the coordinates of the corresponding fixed structure (such as , , , Using a nearest neighbor matching algorithm, each mounting hole is paired with its corresponding fixed structure to generate a matching directory, such as ( , , , This information is used for subsequent spatial constraint calculations and assembly verification. During this process, the system also records the initial deviation vector and direction information for each pair of pairs to determine possible interference directions and spatial distributions.

[0040] In another embodiment, assuming there are a total of 6 mounting hole coordinates, namely... Fixed structural coordinates The system generates a directory by matching ( , , , , , The coordinate deviation vector of each pair of pairs is recorded as [(1.5,0.5,0)mm,(2.0,0.8,0)mm,(1.2,0.6,0)mm,(2.5,1.0,0)mm,(1.8,0.4,0)mm,(2.1,0.9,0)mm], which is used to simulate the spatial matching effect and interference risk analysis in the case of multiple points.

[0041] The spatial distance is calculated based on the matching catalog, and it is determined whether the spatial distance is greater than the preset assembly gap threshold. When the spatial distance is greater than the preset assembly gap threshold, it is recorded as a qualified gap constraint. When the spatial distance is less than or equal to the preset assembly gap threshold, it is recorded as an interference risk constraint. The qualified gap constraints and interference risk constraints are summarized to record the spatial constraint information.

[0042] In one embodiment, the system calculates the Euclidean distance for each pair of paired coordinates, such as Assuming assembly gap threshold ,but The first pair of holes was recorded as a qualified clearance constraint. The other three pairs of distances were 2.83mm, 2.24mm, and 2.83mm, respectively, all greater than the threshold, and were all recorded as qualified clearance constraints. The system finally generates a spatial constraint information table, listing the distance between each pair of mounting holes and the fixed structure, the deviation vector, and the constraint status.

[0043] In another embodiment, an assembly gap threshold is assumed. The spatial distance calculated from the six pairs of paired coordinates is [2.0, 3.1, 2.8, 1.9, 3.0, 2.6] mm. Pairs 1 and 4, which are less than or equal to the threshold, are recorded as interference risk constraints, while pairs 2, 3, 5, and 6 are recorded as acceptable gap constraints. The system summarizes this information in the spatial constraint information table and calculates the interference risk ratio as 33%.

[0044] Preferably, when the spatial distance is less than or equal to a preset assembly gap threshold, after recording it as an interference risk constraint, the following is also included: Interference risk areas are recorded according to interference risk constraints; interference depth values ​​are calculated in interference risk areas; if the interference depth value is greater than a preset first risk threshold, it is determined to be a serious interference risk area; if the interference depth value is less than the preset first risk threshold, it is determined to be a mild interference risk area. In one embodiment, the system first filters out the mounting holes and fixing structures corresponding to interference risk constraints from the aforementioned spatial constraint information, for example, pairing ( Then, based on the CAD 3D model, the interference depth of each pair in the XYZ directions is calculated, such as... The interference depth is 3.2 mm. The interference depth is 1.5 mm. The preset first risk threshold is 2.0 mm. It was identified as an area with a serious risk of interference. The area was identified as having a slight risk of interference. The system simultaneously records the three-dimensional spatial extent of the interference area and the structural components involved, providing a data foundation for subsequent processing.

[0045] In another embodiment, assuming there are a total of 5 points in the interference risk area, with corresponding interference depth values ​​of [1.2, 2.8, 3.5, 0.9, 2.1] mm, and the first risk threshold is still set to 2.0 mm. Points 2, 3, and 5 with depths greater than the threshold are then identified as severe interference risk areas, while points 1 and 4 are identified as mild interference risk areas. This hypothetical scenario is used to simulate the risk distribution and the number of areas at different levels under multi-point interference conditions, providing a reference for assembly optimization and alarm strategies.

[0046] In areas with severe interference risk, interference alarm information is generated, which includes three-dimensional position coordinates, mounting hole markings, and fixed structure markings; in areas with mild interference risk, spatial distance is corrected.

[0047] In one embodiment, the system for An alarm message is generated for areas with severe interference risk: three-dimensional position coordinates (x=10.2mm, y=15.5mm, z=0mm), and mounting hole markings. Fixed structure identifier F1. For areas with slight interference. If the gap is increased by 0.6mm, the spatial distance will be greater than the threshold of 2.0mm, thereby reducing the risk of interference.

[0048] In another embodiment, assuming the areas of severe interference risk are points 2, 3, and 5, the corresponding alarm information generated is as follows: Point 2 location (12.5, 17.3, 0) mm, mounting hole →Fixed structure Point 3, position (15.0, 18.0, 0) mm, mounting hole. →Fixed structure Point 5, position (11.8, 16.5, 0) mm, mounting hole. →Fixed structure For minor interference points 1 and 4, the gaps were increased by 0.5mm and 0.4mm respectively to meet the safety assembly requirements.

[0049] Preferably, constructing an internal component model based on internal component information includes: Extract the core geometry data based on the internal component information; determine the slot positions using the core geometry data; arrange the winding coils according to the slot positions to obtain the winding coil information; and draw the bearing outline based on the internal component information. In one embodiment, the system first obtains the core size parameters (length L=120mm, width W=80mm, height H=50mm) and material boundary information from the design data to construct a three-dimensional geometric model of the core. Then, based on the preset number of slots (e.g., 12 slots) and slot width (5mm), the center position and slot depth of each slot are determined, and the winding coils are arranged around the core, with 50 turns per slot and a wire diameter of 1.2mm, obtaining complete winding arrangement information. Next, using the bearing dimensions (inner diameter 20mm, outer diameter 40mm, height 12mm) and the relative position of the core, the bearing outline is drawn and the installation area is marked, providing basic data for subsequent assembly and internal space analysis.

[0050] In another embodiment, it is assumed that the core is an irregular E-shaped type with 10 slots, each slot being 6mm wide, and the coil has 55 turns per slot with a wire diameter of 1.1mm. The bearing profile is assumed to have an inner diameter of 22mm, an outer diameter of 42mm, and a height of 10mm, with two bearing positions arranged and labeled B1 and B2. This assumption is used to simulate the winding arrangement and bearing space planning under the conditions of multi-slot, irregular core, and bearings of different sizes.

[0051] The bearing installation position is determined based on the bearing profile and winding coil information; the internal component model is constructed based on the bearing installation position and winding coil information.

[0052] In one embodiment, the system calculates the bearing center coordinates (e.g., based on the spatial relationship between the drawn bearing profile and the surrounding coil) (y=40mm, z=25mm), ensuring the mounting surface orientation and coil clearance meet safety assembly requirements. Then, the bearing, winding, and core are assembled to construct a complete internal component model, including coil winding layers, core geometry, and bearing mounting position information, forming a three-dimensional model suitable for assembly simulation and magnetic field analysis.

[0053] In another embodiment, assume the mounting center coordinates of bearing B1 are (62, 38, 24) mm, and those of bearing B2 are (58, 42, 26) mm. The winding coil information includes 55 turns per slot, a wire diameter of 1.1 mm, and a 10-slot arrangement. Importing the assumed data into 3D modeling software, an internal component model is constructed, showing a minimum clearance of 2 mm and a maximum clearance of 3.5 mm between the bearing and the winding.

[0054] Most importantly, determining the bearing mounting location based on the bearing profile and winding coil information includes: Calculate the bearing outer diameter based on the bearing profile; determine the bearing radial mounting position based on the bearing outer diameter; divide the space occupied area based on the winding coil information, and perform collision analysis to identify potential interference points; In one embodiment, the bearing outer diameter (e.g., 50mm) is first calculated using the bearing contour data from the internal component model. Then, combined with the stator slots and rotor geometry, the radial mounting position of the bearing is determined, aligning the bearing centerline with the rotor's rotation axis. Subsequently, based on the spatial arrangement information of the winding coils, the internal space is divided into three dimensions to establish a space occupancy model. Collision analysis is performed between the bearing, rotor, and windings. Simulation software scans the entire rotation range to identify possible interference points (such as coil contact with the bearing edge) and records their coordinates and interference types.

[0055] In another embodiment, assuming the calculated bearing outer diameter is 48mm, the radial mounting position is initially determined to be 25mm from the rotor axis. Based on the mesh model of the winding space occupancy (each grid side length 2mm), collision analysis reveals a total of 12 potential interference points, distributed at the upper end of the winding and the edge of the bearing outer ring. The interference depth is assumed to be between 0.5 and 1.2mm, which will be used for subsequent adjustments to the bearing installation and internal component clearance design.

[0056] Of particular importance is the division of space occupancy areas based on winding coil information, and the performance of collision analysis to identify potential interference points, including: The slot winding area and the end winding area are extracted based on the winding coil information. The slot winding area and the end winding area are the space-occupied areas. Virtual collision detection is performed on the slot winding area and the end winding area. When contact between the two is detected, the axial clearance distance between the slot winding area and the end winding area is calculated. In one embodiment, firstly, based on the three-dimensional geometric model of the stator winding, the in-slot winding area (located within the stator slot) and the end winding area (located at the end flange) are extracted to establish a three-dimensional space occupancy model. Subsequently, a virtual collision detection algorithm is used to scan the two areas within the entire winding deployment range. When contact or overlap is detected, the axial clearance distance at the contact point is calculated (e.g., measured to be 0.8 mm) to assess potential interference that may occur during assembly or thermal expansion of the winding.

[0057] In another embodiment, assuming that the slot winding area and the end winding area are represented by 1500 and 1200 discrete grid points respectively, 30 potential contact points are identified by virtual collision detection. The axial clearance distance is calculated for each contact point, and the clearance range is 0.5–1.3 mm. The minimum value of 0.5 mm corresponds to the local contact between the top winding of the slot and the end winding, and the maximum value of 1.3 mm corresponds to the far end position between the end winding and the adjacent slot winding.

[0058] When the axial clearance distance is less than the preset contact distance, it is marked as a potential interference point.

[0059] In one embodiment, a preset contact distance of 1.0 mm is set, and the calculated axial clearance distance is compared. When the distance is less than 1.0 mm, the position is marked as a potential interference point, and its three-dimensional coordinates and interference type are recorded for subsequent assembly adjustment and optimization design.

[0060] In another embodiment, assuming that among the 30 detected axial clearance distances, 18 points are less than 1.0 mm (range 0.5–0.95 mm), these points are marked as potential interference points, while the remaining 12 points with clearances greater than 1.0 mm are not treated as interference points. Potential interference points are distributed in the end region of the slot winding and adjacent to the top of the end winding, and can be used for subsequent axial displacement adjustments or winding layout optimization.

[0061] Calculate the spatial deviation based on potential interference points; determine the axial displacement range based on the spatial deviation; determine the axial installation position of the bearing based on the axial displacement range; calibrate the bearing installation position based on the bearing radial installation position and the bearing axial installation position.

[0062] In one embodiment, based on the identified potential interference points, the spatial deviation (such as deviation vector and magnitude) of each interference point relative to the design geometry is calculated, and an allowable displacement range (such as ±1 mm) is generated in the axial direction to adjust the bearing position and avoid interference. Subsequently, the optimal installation position is selected within the allowable axial displacement range to maintain a safe clearance between the bearing and the rotor, stator, and windings, while meeting rotational accuracy requirements. Finally, combined with the radial position, the complete installation position of the bearing is calibrated in the three-dimensional model.

[0063] In another embodiment, assuming the potential interference point deviation is within the range of 0.5–1.2 mm, the axial installation position of the bearing is determined to be 10 mm from the shaft end face after axial displacement adjustment, with an allowable axial displacement range of ±0.8 mm. Combined with the radial installation position of 25 mm, the bearing is calibrated in the three-dimensional model to obtain the complete installation coordinates (x, y, z) = (25, 0, 10) mm, which are used for subsequent assembly verification and three-dimensional simulation analysis.

[0064] Preferably, constructing a 3D simulation model using spatial constraint information and internal component models includes: The internal component models are constrained according to spatial constraints, and rotational degrees of freedom are set; motion simulation is performed using rotational degrees of freedom, and angular displacement data is recorded; In one embodiment, the system first fixes the internal component models (including rotor, core, bearings, and couplings) in three-dimensional space according to design constraints, such as fixing the bearing mounting surface to the frame and fixing the coil windings in slots, and setting the rotor's rotational degree of freedom around the shaft. Then, it uses dynamic simulation software (such as ADAMS or SimscapeMultibody) to simulate the rotor's motion, recording angular displacement data during the simulation. The rotor angular displacement is recorded every 1ms, with a total simulation duration of 2s, resulting in a continuous angular displacement sequence used for subsequent speed calculation and inertia analysis.

[0065] In another embodiment, it is assumed that the rotor mass in the internal component model is 3.5 kg, the bearing positions are (62, 38, 24) mm and (58, 42, 26) mm, and the initial speed is 1500 rpm. The simulation is set to a total duration of 3 s and a sampling interval of 2 ms, resulting in an angular displacement sequence [0°, 0.5°, 1.1°, 1.8°, 2.6°, ..., 180°] (a total of 1500 sampling points).

[0066] Calculate the instantaneous rotor speed based on angular displacement data; adjust the rotational inertia of the internal component model based on the instantaneous rotor speed; construct a three-dimensional simulation model based on the rotational inertia and the internal component model.

[0067] In one embodiment, the instantaneous rotational speed ω(t) = dθ(t) / dt at each sampling moment is calculated using the recorded angular displacement sequence through numerical differentiation, and the data is filtered to remove high-frequency noise. Based on the rotor's instantaneous rotational speed, the rotational inertia of the rotor and related components is adjusted to simulate dynamic inertial effects. Finally, the internal component model with corrected rotational inertia is imported into 3D simulation software to construct a complete 3D simulation model for analyzing dynamic response, rotor vibration, and component stress conditions.

[0068] In another embodiment, it is assumed that the instantaneous rotor speed sequence is calculated from angular displacement data as follows: (A total of 1500 data points) Adjust the rotor's rotational inertia according to speed fluctuations. arrive The amplitude varies between these values. A three-dimensional simulation model built using this hypothetical data shows that the rotor amplitude decreases by about 5% under high inertia and increases by about 7% under low inertia, which is used to verify the impact of inertia adjustment on dynamic performance.

[0069] Please see Figure 2 The core structure of the servo motor 3D simulation model is shown. The front end is a circular flange with mounting holes and a central output shaft. The main body housing has heat dissipation fins to assist in heat dissipation. The top integrates components with interfaces and lead-out cables, which is a typical industrial servo motor structure, combining power output and high-precision control functions.

[0070] Preferably, in step S2, the test control direction is input into the three-dimensional simulation model, and the output simulation signal of the servo motor includes: Start the 3D simulation model, input the test control direction into the 3D simulation model, and output the velocity feedback signal and the current feedback signal; perform integration processing on the velocity feedback signal to obtain the velocity simulation curve; In one embodiment, a 3D model of the servo motor is first launched in the simulation environment, including complete dynamic parameters of the rotor, stator, and controller. A preset test control direction (such as forward rotation, reverse rotation, or positioning command) is input into the 3D simulation model, and speed feedback signals and current feedback signals are output in real time. The speed feedback signals are then integrated to obtain a continuous speed simulation curve, and the speed value is recorded every 1ms for analyzing torque response, acceleration / deceleration performance, and control accuracy.

[0071] In another embodiment, assuming the test control direction is a forward rotation of 180°, the total simulation duration is 2 seconds, and the velocity feedback signal is recorded at a sampling interval of 2 ms to obtain the sequence [0, 0.12, 0.25, 0.37, 0.51, ..., (A total of 1000 sampling points). The velocity simulation curve was obtained by integrating the sequence. The maximum acceleration is about 120 rad / s². The simulation curve is used to evaluate the rotational performance and dynamic response characteristics under different control directions and initial states.

[0072] The current feedback signal is filtered to obtain the current simulation curve; the speed simulation curve and the current simulation curve are integrated to obtain the simulation signal of the servo motor.

[0073] In one embodiment, the obtained current feedback signal is processed through a low-pass filter (e.g., with a cutoff frequency of 500Hz) to eliminate high-frequency noise and measurement jitter, generating a continuous current simulation curve. Subsequently, the speed simulation curve and the current simulation curve are integrated in time synchronization to form a complete simulation signal sequence for the servo motor, which can be used for control algorithm verification, load response analysis, and system optimization.

[0074] In another embodiment, assuming the current feedback signal sampling sequence is [0, 1.2, 2.5, 3.7, 5.0, ..., 12A] (a total of 1000 points), a smooth current curve is obtained after low-pass filtering with a cutoff frequency of 500Hz. Integrating this current curve with the speed simulation curve yields the final simulation signal, where the maximum current peak of 12A corresponds to the speed... This information can be used for subsequent control strategy evaluation and system performance optimization.

[0075] It should be noted that, please refer to Figure 3 The diagram illustrates a structural block diagram of a terminal device 1900 provided in one embodiment of this application. The terminal device 1900 can be any electronic device with data computing, processing, and storage functions. The terminal device 1900 can be used to implement a servo motor modeling and simulation method provided in the above embodiments.

[0076] Typically, terminal device 1900 includes a processor 1901 and a memory 1902.

[0077] Processor 1901 may include one or more processing cores, such as a quad-core processor, an octa-core processor, etc. Processor 1901 may be implemented using at least one hardware form selected from DSP (Digital Signal Processing), FPGA (Field Programmable Gate Array), and PLA (Programmable Logic Array). Processor 1901 may also include a main processor and a coprocessor. The main processor, also known as a CPU (Central Processing Unit), is used to process data in the wake-up state; the coprocessor is a low-power processor used to process data in the standby state. In some embodiments, processor 1901 may integrate a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content required to be displayed on the screen. In some embodiments, processor 1901 may also include an AI (Artificial Intelligence) processor, which is used to handle computational operations related to machine learning.

[0078] The memory 1902 may include one or more computer-readable storage media, which may be non-transitory. The memory 1902 may also include high-speed random access memory and non-volatile memory, such as one or more disk storage devices or flash memory devices. In some embodiments, the non-transitory computer-readable storage media in the memory 1902 is used to store a computer program configured to be executed by one or more processors to implement a servo motor modeling and simulation method.

[0079] Those skilled in the art will understand that Figure 3 The structure shown does not constitute a limitation on the terminal device 1900, and may include more or fewer components than shown, or combine certain components, or use different component arrangements.

[0080] Therefore, the embodiments should be considered as exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, it is intended that all variations falling within the meaning and scope of the equivalents of the application be incorporated into the invention.

[0081] The above description is merely a specific embodiment of the present invention, enabling those skilled in the art to understand or implement the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the present invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features of the invention herein.

Claims

1. A method of modeling and simulation of a servo motor, characterized by, Includes the following steps: Step S1: Initialize the control parameters of the servo motor; perform control direction verification using the control parameters and record the encoder feedback signal; determine the test control direction based on the encoder feedback signal and the control parameters; Step S2: Obtain servo motor design data and construct a three-dimensional simulation model based on the servo motor design data; input the test control direction into the three-dimensional simulation model and output the simulation signal of the servo motor; Step S3: Calculate the rotor oscillation amplitude based on the simulation signal; If the rotor oscillation amplitude exceeds the preset oscillation amplitude, the signal phase of the simulation signal is corrected, and the corrected simulation signal is output.

2. The modeling and simulation method of a servo motor according to claim 1, wherein, The control parameters for initializing the servo motor in step S1 include: On the servo motor control card side, select the target control mode, initialize the proportional, integral and derivative parameters in the target control mode to zero values, and save them as the initial control configuration; On the servo motor side, set the control mode and the proportional coefficient between the control signal and the motor speed in the control mode; use the initial control configuration and the proportional coefficient as the control parameters of the servo motor.

3. The modeling and simulation method of a servo motor according to claim 1, wherein, In step S1, control direction verification is performed using control parameters, and the encoder feedback signal is recorded, including: The control parameters are sent to the servo motor, and the speed is calculated. The speed is compared with the preset zero drift threshold. When the speed is greater than the zero drift threshold, the offset compensation value is adjusted. The control direction is determined using the offset compensation value. The control direction is sent to the servo motor, and the encoder feedback signal is recorded.

4. The modeling and simulation method of a servo motor according to claim 1, wherein, Step S1, determining the test control direction based on the encoder feedback signal and control parameters, includes: When the encoder feedback signal is a positive feedback signal, the original control direction identifier in the control parameters is maintained; When the encoder feedback signal is a reverse feedback signal, the original control direction identifier is inverted and the corrected direction identifier is recorded. The corrected direction identifier is written into the control parameters, overwriting the original control direction identifier, in order to determine the test control direction.

5. The modeling and simulation method of a servo motor according to claim 1, wherein, Step S2 involves acquiring servo motor design data and constructing a 3D simulation model based on that data, including: Acquire servo motor design data, including motor housing dimensions and internal component information; draw the motor housing outline based on the motor housing dimensions, and add mounting holes and fixing structures to the motor housing outline; use the mounting holes and fixing structures to perform assembly clearance verification to record spatial constraint information; An internal component model is constructed based on the internal component information; a three-dimensional simulation model is constructed using spatial constraint information and the internal component model.

6. The modeling and simulation method of a servo motor according to claim 5, wherein, Assembly clearance verification is performed using mounting holes and fixing structures to record spatial constraint information, including: Determine the coordinates of the mounting holes; read the coordinates of the fixed structure; match the coordinates of the mounting holes and the fixed structure, and generate a matching directory; The spatial distance is calculated based on the matching catalog, and it is determined whether the spatial distance is greater than the preset assembly gap threshold. When the spatial distance is greater than the preset assembly gap threshold, it is recorded as a qualified gap constraint. When the spatial distance is less than or equal to the preset assembly gap threshold, it is recorded as an interference risk constraint. The qualified gap constraints and interference risk constraints are summarized to record the spatial constraint information.

7. The modeling and simulation method of a servo motor according to claim 6, wherein, When the spatial distance is less than or equal to the preset assembly gap threshold, it is recorded as an interference risk constraint, and the following is also included: Interference risk areas are recorded according to interference risk constraints; interference depth values ​​are calculated in interference risk areas; if the interference depth value is greater than a preset first risk threshold, it is determined to be a serious interference risk area; if the interference depth value is less than the preset first risk threshold, it is determined to be a mild interference risk area. In areas with severe interference risk, interference alarm information is generated, which includes three-dimensional position coordinates, mounting hole markings, and fixed structure markings; in areas with mild interference risk, spatial distance is corrected.

8. The modeling and simulation method of a servo motor according to claim 5, wherein, Constructing an internal component model based on internal component information includes: Extract the core geometry data based on the internal component information; determine the slot positions using the core geometry data; arrange the winding coils according to the slot positions to obtain the winding coil information; and draw the bearing outline based on the internal component information. The bearing installation position is determined based on the bearing profile and winding coil information; the internal component model is constructed based on the bearing installation position and winding coil information.

9. The modeling and simulation method of a servo motor according to claim 5, wherein, Constructing a 3D simulation model using spatial constraint information and internal component models includes: The internal component models are constrained according to spatial constraints, and rotational degrees of freedom are set; motion simulation is performed using rotational degrees of freedom, and angular displacement data is recorded; Calculate the instantaneous rotor speed based on angular displacement data; adjust the rotational inertia of the internal component model based on the instantaneous rotor speed; construct a three-dimensional simulation model based on the rotational inertia and the internal component model.

10. The method of claim 1, wherein In step S2, the test control direction is input into the three-dimensional simulation model, and the output simulation signal of the servo motor includes: Start the 3D simulation model, input the test control direction into the 3D simulation model, and output the velocity feedback signal and the current feedback signal; perform integration processing on the velocity feedback signal to obtain the velocity simulation curve; The current feedback signal is filtered to obtain the current simulation curve; the speed simulation curve and the current simulation curve are integrated to obtain the simulation signal of the servo motor.

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